Surging data demand driven by the mobile devices mind-set of consumers, the proliferation of smartphones and onset of the use of applications (“apps”) on mobile devices is revolutionising the mobile industry. In 2010, smartphones accounted for more than 30 percent of total wireless handset sales. The uptake in smartphone usage is mostly driven by mobile apps, which, while using Internet in the background, offer a personalised experience to the user. A study from the Pew Internet Project illustrates that one in four US adults use mobile apps. App users had an average of 18 apps on their devices and a median of 10, the study estimates.
However, due to the open nature of apps ecosystem, any developer can upload an application to the source of applications (e.g. Android Market or Apple's App store) without any quality assurance checks. This results in a large number of malicious applications making their way to smartphones that attempt to take advantage of user's proclivity to ignore permissions and other warning signs and install whatever looks good to them. Some of the apps are truly dangerous, while others are simply not well written—e.g. not optimised so that they consume excessively device battery power and/or the user's data allowance (such as by sending unnecessary traffic to the network).
Current methods of rating applications are typically very simplistic. Typically, applications are rated according to how many times they have been downloaded. This is not particularly useful to a user, as applications that are downloaded frequently, may be deleted shortly thereafter if they are unsatisfactory.
Today, an important proportion of returned smartphones is the result of problems with apps and software, rather than hardware. Moreover, in a smartphone dominated marketplace, the performance of mobile apps is regarded as an important component of network operator selection and customer loyalty. It would be advantageous to offer a capability to users to make informed decisions while downloading applications, monitor real time apps performance, control their privacy and properly manage the apps on their smartphones. Moreover, with a better visibility of customer's smartphones apps performance, network operators could take predictive customer actions (e.g to offer customers upgraded services) through product and channel intervention.
Raw data collection gathering software is known in the form of an application which a user can download on their smartphone (or may be pre-installed) that interacts with other applications running on the smartphone in real-time (in the background) and monitors their performance in terms of battery consumption, CPU usage, data consumption, user privacy settings and app experience (data rate, latency). However, although such an application can collect data, it does not use/analyse the data to improve the user experience or network performance, and nor does it offer a solution for monetising the data.
It is in theory possible for the core of a mobile telecommunications network to analyse data sent to/from mobile terminal applications but it is difficult to identify to which application data relates, and impracticable to identify traffic relating to a particular application relating and to a particular mobile device user. Analysis at the network core, even if possible, does not provide representative data of application use as about 80% of data traffic from mobile terminals is currently transmitted over WLAN radio access networks rather that cellular networks.